Healthcare strategy

We shipped our MCP server and AI Assistant Suite, and adoption exceeded targets. The surprise? AI tooling generates more backlog, not less. When it’s cheaper to propose an integration change, more changes get proposed and freed-up capacity gets absorbed by work that never made the cut before.

CTO Sasi Mukkamala breaks down what changed, what didn’t, and where our AI roadmap goes next.

Redox CPO Rachel Witalec recently joined Intellistack for an episode of Partner Pulse, a series exploring how technology partners are solving healthcare’s hardest integration challenges. This piece goes deeper on what Rachel covered: why the data infrastructure layer determines whether activation tools actually work in production, and what that means for the healthcare IT teams evaluating them.

Evaluating an interoperability partner? Ask these non-obvious questions about resource costs, scaling, and data usability before you sign.

The most productive integration engineers have stopped logging into platforms. In this post, Redox CPO Rachel Witalec makes the case for headless healthcare data infrastructure: what it requires, what it unlocks, and why most platforms can’t pull it off.

Most healthcare organizations have solved the data movement problem. The harder challenge (and the one AI actually requires) is data readiness. In this post, Redox CPO Rachel Witalec breaks down the three jobs of AI-ready healthcare data infrastructure and what it takes to build a composability layer that lets AI work reliably at scale.

Stop paying staff to manually triage paper. See how thin-margin health systems use intelligent document automation to slash operating costs and scale in just 35 days.

After seven years at Redox, Andy Pung left. Now, he’s back as Head of Sales. Discover why his return wasn’t just about the incredible culture, but how the Redox platform has evolved from a startup point solution into a powerhouse for enterprise healthcare data orchestration and AI adoption.

Why vibe-coded AI fails in production: beyond the “time-to-wow” demo trap. Discover why healthcare AI integrations need more than just foundational models. Learn how an agent harness and real-world EHR expertise bridge the gap between a polished prototype and production-ready interoperability.

Healthcare interoperability has a new mandate. Learn why AI success depends on intraoperability — the internal data infrastructure that turns fragmented systems into an agentic enterprise.

Since it’s February, the month of love, we can’t help but notice that scaling a healthcare data integrations team feels a lot like dating. And just like dating, the goal isn’t a flashy first impression; it’s a partner who shows up consistently, adapts as you grow, and stays steady when things get complicated. You deserve an interoperability partner who’s in it for the long haul, not just a phase.

Point solutions are built to optimize for a vertical set of use cases. Interoperability partners create the conditions for many. The difference matters more as healthcare organizations look to apply analytics, automation, and AI at scale. Without a strong interoperability foundation, teams spend more time rebuilding plumbing than improving care.

Meet Sasi Mukkamala, Redox’s new CTO. After years building AI-powered products that rely on clean upstream data, Sasi joined Redox to help elevate our platform into the intelligent foundation healthcare needs for AI at scale. Sasi’s debut post shares why Redox’s intelligent platform is uniquely positioned to deliver real operational value through AI.